It is presently common to use images of a scene for monitoring thereof, including, inter alia, usage of SAR (Synthetic Aperture Radar) images for that purpose. Computerized processing of such images involves image processing.
Those versed in the art of image processing are familiar with the requirement to register two or more images of a scene. There are known techniques for image registration. See, for example, Barbara Zitová and Jan Flusser's “Image registration methods: a survey” (Image and Vision Computing 21, 2003, pages 977-1,000), presenting several such methods.
However, it sometimes happens that one or more images suffer from occlusion, poor contrast etc., which disturb interpretation or processing of the data included therein. Partial and basic handling of such cases is presently done in the art.
Quality assessment of images is dealt with, for example, in the article “Image Quality Assessment: from Error Visibility to Structural Similarity” (IEE transactions on image processing, Vol 13, No 4, April 2004), by Wang et al., who teach a method for quality assessment of images based on the degradation of structural information.
Another example is, Alberto Moreira's “Improved Multilook Techniques Applied to SAR and SCANSAR Imagery” (IEEE Transactions on Geoscience and Remote Sensing, Vol. 29, No 4, July 1991), suggesting techniques for multilook processing. These techniques are based on the formation of looks with different bandwidths. The final image is formed by giving each look a proper size and weighting and by adding them incoherently.
In chapter 5 of their book “Computer Vision”, Linda Shapiro and George Stockman teach a method for filtering and enhancing images.
Image processing and enhancement of images require different techniques, sometimes taken from other fields of technology. For example, in the field of decision making full reinforcement operators and reinforcement learning are known algorithms that combine fuzzy logic and reinforcement learning.